Textbook:Introduction to
Stochastic Integration, K. L. Chung and R. J. Williams, 2nd edition. There may also be some extra notes which will be
distributed on this web-page at "Lecture Notes."
Prerequisites: Math 280A-B or consent of the instructor.

Homework: There will be a few home
works throughout the quarter.

Grading: Final Grade = homework and
attendance.

Description: Stochastic differential equations (SDE) can be used
to model a variety of random dynamic phenomena in the physical, biological,
engineering and social sciences. Solutions of these equations are often Markov
diffusion processes. Because of this SDE theory has strong links to the
classical theory of partial differential equations (PDE).

Stochastic differential equations arise in modeling
a variety of random dynamic phenomena in the physical, biological, engineering
and social sciences. Solutions of these equations are often diffusion processes
and hence are connected to the subject of partial differential equations. This
course will present the basic theory of stochastic differential equations and
provide examples of its application.